DOCSLIB.ORG

Attack Patterns on Iot Devices Using Honey Net Cloud

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Attack Patterns on Iot Devices Using Honey Net Cloud International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-9 Issue-2, December 2019 Attack Patterns on IoT devices using Honey Net Cloud A R Jayakrishnan, V.Vasanthi calculated to fingerprint the IoT malware, and such Abstract: Due to the superfluous growth of IoT devices in the fingerprints could be shared with the community over current digital world, where lots of devices are becoming smart by VirusTotal1. Static and dynamic analysis can be applied for being able to connect internet with many smart features, IoT the malwares those are not been fingerprinted to regulate devices have become the main target of cyber-attacks for the their malevolence [5]. hackers these days. Since the IoT devices are very light in terms of File-less attacks which is also called as non-malware processing power and memory, it has become an easy target for hackers to intrude in to the network easily. The file-less attacks, attacks or zero footprint attacks on IoT things vary from that usually doesn’t require any files to be downloaded and malware based attacks, where they need not download and installed gets bypassed by anti-malwares. Very less effort has been run malware files to infect the IoT devices; but instead they put to learn the characteristics of attack patterns in IoT devices to take benefit of existing vulnerabilities on the victims‟ devices do the research and development efforts to defend against them. and intrude in to the network. For the past few years, This paper deep dives to understand the attacks on IoT devices in progressively more and more file-less attacks were reported the network. HoneyNetCloud has been made with four hardware [6]. McAfee Labs reported that file-less attacks ramped up by honeypots and hundred software honeypots setup that are meant 430% by 2017 [7]. For the PCs, laptops and servers, to attract wide variety of attacks from the real world. Huge range defending file-less attacks can be easily done by using anti of data was recorded for the span of 12 months. This study leads to multifold insights towards developing the IoT Network Forensics malware tools, firewalls and antivirus apps [8]; however, Methodology. since due to the limited computing, storage and memory Keywords: IoT attack, Network Forensics, Honeypots, Digital capacity for the vast majority of IoT things, such antivirus Security, HoneyNetCloud, Intrusion. solutions are not suitable. As the result, file-less attacks stance substantial threats to the IoT ecosystem. Remember I. INTRODUCTION that the IoT things are often deployed in private and sensitive Internet of Things has rapidly enlarged popularity across environments, such as banks, military areas, government a wide range of areas in home automation, industrial smart offices, private residences and healthcare centres. There is sensing and control etc [2]. In general, most of today‟s IoT very limited visibility into their appearances and attack smart devices employs the Linux (eg. Raspbian and vectors at the moment, which hampers research and OpenWrt) for its programmability and prevalence [1]. development efforts to innovate new defence to battle Connected things however incessantly emit stream of data as file-less attacks [9] part of their communication in the network. Meanwhile, the A. Methodology cyber-attacks volume also increases rapidly. This paper therefore concentrates on Linux based IoT things and the In this research, I‟ve used honeypots, which are effective intrusions targeting them. In general, there are two types of to capture the unknown network attacks by attracting attacks on IoT things: File-less attacks and Malware based intruders to the network [10]. Initially, four hardware attacks [3]. honeypots were setup. Each of them was attached with a Malware based attacks are very common these days. remote control power adapter, which has the ability to reset Examples like PNScan, Mirai and Mayday have been broadly the honeypot when it is compromised to attacks. These acknowledged in IoT networks. Popular and commonly used indeed provided valuable insights in to the IoT attacks at the websites like Twitter, Github were inaccessible for many same time they are very expensive to setup too. In order to hours during Oct 2016, when their DNS provider attacked by attract more and more real-time attacks, I‟ve decided to scale Mirai under DDOS attack. This was infected over 1.2 million up the number of honeypots connected in a much cheaper and IoT things over the world [4]. Such alarming incidents effective way by installing virtual honeypots. Hundreds of created high alerts among investigators and researchers about software virtual honeypots were setup that are meant to malware based attacks on IoT systems; Their characteristics attract wide variety of attacks from the real world. With the have been extensively studied over past few years and hence ever growing cloud setup around the globe with various effective defence solutions were developed. For example, the providers, it seemed to be a possible solution for me in my hash MD5 or SHA-n of a malware‟s binary file can be approach as its both economical and practical to implement. However, there are a few practical concerns to this. Firstly, Revised Manuscript Received on December 05, 2019. the software honeypots should behave likewise to the actual * Correspondence Author IoT devices, so that it won‟t miss any sort of attacks. A. R Jayakrishnan*, Research Scholar, RCAS, Bharathiar University, Secondly, they should also be able to depict comprehensive Coimbatore, Tamilnadu. India V.Vasanthi, Assistant Professor, Dept of IT, SKASC, Coimbatore, data of the interaction methods, so that it will become easy to Tamilnadu, India categorize the difficult to track attacks. Finally, they have to go Published By: Retrieval Number: B6591129219/2019©BEIESP Blue Eyes Intelligence Engineering DOI: 10.35940/ijitee.B6591.129219 3281 & Sciences Publication Attack Patterns on IoT devices using HoneyNetCloud along with the diverse policies imposed by the cloud attackers. It has been observed that 9231 attacks providers, so that limitations of clouds will not really impact executed commands like lscpu to extract very each other for the coverage of the study results. Hence, the sensitive information. This is derived from the design of the software honeypots was customized by measurements taken from the hardware honeypots incorporating the comprehensions composed from hardware setup as part of the implementation. Whereas in the honeypots, such as the encrypted command disclosure, kernel software honeypots HoneyNetCloud, an average of information masking and data flow symmetry monitoring. 6.9% fewer attacks were captured by the honeypot I‟ve carefully selected eight public clouds to disperse hosted on AWS than other public clouds. This could hundred software honeypots, and group of the developed be because AWS reveals IP range of all its VM system is called HoneyNetCloud. All of the software instances. Some of the malwares like Mirai will not honeypots in the HoneyNetCloud have been employed with infect specific IP range [12]. These comprehensions DD-WRT, which is the best and most popular Linux based were incorporated to improve the effectiveness and OpenSource firmware for IoT devices [11] and is also reliability of the design of HoneyNetCloud. appropriate for customization.In comparison with the . More file-less attacks due to the unique types of hardware honeypot, a virtual honeypot attracts 35% lesser attacks. Most difficult, powerful and dangerous suspicious connections and 37% lesser attacks on an average threats are observed to be file-less attacks. 41.2% of basis. However, the maintenance cost for the software the attacks are considered to be gathering system version is 12 times less compared to that of the hardware information and/or performing activities shutting honeypot. Interestingly, all the attacks trapped by the down firewalls, deactivating watchdog and stopping hardware honeypots have also been captured and trapped by antivirus services etc. This is considered to be done so the HoneyNetCloud, but this is not the other way round. This as to get clear way for consecutive attacks and also to proves the effectiveness of my design in practice. allow more targeted attacks. The pattern of attacks shows that the most favourite attack by hackers is B. Implications discovered from the findings file-less since they are difficult to fingerprint and Honeypots were run for a span of one year (i.e 02/Oct/2018 hence most suitable for cautious attack to 01/Oct/2019). The suspicious connections to the reconnaissance and preparations. In the attack honeypots were around 286 million in the time span of one metrics, there was also a targeted DDoS attack, that year. Out of which, 34 million (11.88%) successfully logged neither touches the filesystem nor run any shell and able to attack. The rest of 88.12% observed suspicious commands, however it manipulates a flock of IoT could not intrude to the honeypots, since they fail to crack the devices and make the attackers not visible to victims. passwords. Among the successful intrusion attaks, 2.5 The anomalous pattern of outbound network traffic is million were classified as file-less attacks and rest of them as the only indication of such attacks. It is highly malware attacks. promising for the existing host based tracking or . New security challenges by the file-less attacks monitoring system to catch it effectively. could be discovered and thus leads to propose new . Classification of eight types of attacks. The detailed defence directions. Most of the captured attacks were study of attack patterns and data captured for the using shell commands, hence they were all detectable duration of one year has provided the way to by auditing the command history in the IoT devices. categorise the IoT attacks in to eight different types. Most of the IoT devices use a readonly filesystem so Due to the lack of malware files and fingerprints, it that the malware based attacks could reduce, however was never an easy task to classify and also to identify this unpredictably increases the difficulty of detecting the attack patterns.
Load more

Recommended publications
  • Malware Trends
    NCCIC National Cybersecurity and Communications Integration Center Malware Trends Industrial Control Systems Emergency Response Team (ICS-CERT) Advanced Analytical Laboratory (AAL) October 2016 This product is provided subject only to the Notification Section as indicated here:http://www.us-cert.gov/privacy/ SUMMARY This white paper will explore the changes in malware throughout the past several years, with a focus on what the security industry is most likely to see today, how asset owners can harden existing networks against these attacks, and the expected direction of developments and targets in the com- ing years. ii CONTENTS SUMMARY .................................................................................................................................................ii ACRONYMS .............................................................................................................................................. iv 1.INTRODUCTION .................................................................................................................................... 1 1.1 State of the Battlefield ..................................................................................................................... 1 2.ATTACKER TACTIC CHANGES ........................................................................................................... 2 2.1 Malware as a Service ...................................................................................................................... 2 2.2 Destructive Malware ......................................................................................................................
    [Show full text]
  • A Malicious Concept That Conquered the Elf Format
    DDOS TROJAN: A MALICIOUS fl ooding tools) that provides an attacker with the possibility of forming a malicious botnet. The framework consists of C&C CONCEPT THAT CONQUERED panels, bot builders, installation scripts, port scanners, SSH THE ELF FORMAT brute-forcers, etc. In our paper we provide a survey of current Linux DDoS bots and we sketch a wider context of usage of Peter Kálnai & Jaromír Hořejší the above-mentioned components. This topic has been covered Avast Software, Czech Republic by many independent security researchers, e.g. the MalwareMustDie! group summarised their series of blogposts Email {kalnai, horejsi}@avast.com in [2]. The authors presented its early development in [21]. 2. COMMON CHARACTERISTICS ABSTRACT DDoS threats have been around ever since the Internet took 2.1 About the ELF format over half of global communications, posing the real problem of ELF is short for ‘Executable and Linkable Format’, which is a denial of access to online service providers. Recently, a new common standard format for executables under Unix systems. trend has emerged in non-Windows DDoS attacks that has been The instruction set architecture (ISA) of the binary is stored at induced by code availability, lack of security and an abundance the offset e_machine, and we refer to this parameter using the of resources. The attack infrastructure has undergone prefi x ‘EM_’. Unix systems power not only desktop and server signifi cant changes in structure, function and complexity. machines, but are also the main operating systems for Malware has evolved into complex and relatively sophisticated embedded devices. Although Intel 80386 (EM_386) and pieces of code, employing compression, advanced encryption AMD64 (EM_x86_64) ISAs are the most common for desktops and even rootkit capabilities.
    [Show full text]
  • An Automated and Comprehensive Framework for Iot Botnet Detection and Analysis (Iot-BDA)
    This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2021.3110188, IEEE Access Digital Object Identifier 10.1109/ACCESS.2017.DOI An Automated and Comprehensive Framework for IoT Botnet Detection and Analysis (IoT-BDA) TOLIJAN TRAJANOVSKI1, NING ZHANG1 1Department of Computer Science, University of Manchester, M13 9PL UK Corresponding author: Tolijan Trajanovski (e-mail: [email protected]). ABSTRACT The proliferation of insecure Internet-connected devices gave rise to the IoT botnets which can grow very large rapidly and may perform high-impact cyber-attacks. The related studies for tackling IoT botnets are concerned with either capturing or analyzing IoT botnet samples, using honeypots and sandboxes, respectively. The lack of integration between the two implies that the samples captured by the honeypots must be manually submitted for analysis in sandboxes, introducing a delay during which a botnet may change its operation. Furthermore, the effectiveness of the proposed sandboxes is limited by the potential use of anti-analysis techniques and the inability to identify features for effective detection and identification of IoT botnets. In this paper, we propose and evaluate a novel framework, the IoT-BDA framework, for automated capturing, analysis, identification, and reporting of IoT botnets. The framework consists of honeypots integrated with a novel sandbox that supports a wider range of hardware and software configurations, and can identify indicators of compromise and attack, along with anti-analysis, persistence, and anti-forensics techniques. These features can make botnet detection and analysis, and infection remedy more effective.
    [Show full text]
  • Iot Vulnerabilities Easily 5
    • Babak D. Beheshti, Associate Dean of the School of Engineering and Computing Sciences at NYIT. • Clyde Bennett, Chief Healthcare Technology Strategist at Aldridge Health. • Ross Brewer, VP and MD of EMEA at LogRhythm. • Ben Desjardins, Director of Security Solutions at Radware. • Eric O'Neill, National Security Strategist at Carbon Black. • Jeff Schilling, Chief of Operations and Security at Armor. • Karl Sigler, Threat Intelligence Manager at Trustwave. • Sigurdur Stefnisson, VP of Threat Research at CYREN. • Amos Stern, CEO at Siemplify. • Ronen Yehoshua, CEO at Morphisec. ! Visit the magazine website at www.insecuremag.com Feedback and contributions: Mirko Zorz, Editor in Chief - [email protected] News: Zeljka Zorz, Managing Editor - [email protected] Marketing: Berislav Kucan, Director of Operations - [email protected] (IN)SECURE Magazine can be freely distributed in the form of the original, non-modified PDF document. Distribution of modified versions of (IN)SECURE Magazine content is prohibited without permission. ! Copyright (IN)SECURE Magazine 2016. www.insecuremag.com Are all IoT vulnerabilities easily 5. Insecure or no network pairing control op- avoidable? tions (device to device or device to net- works). Every vulnerability or privacy issue reported 6. Not testing for common code injection ex- for consumer connected home and wearable ploits. technology products since November 2015 7. The lack of transport security and encrypt- could have been easily avoided, according to ed storage including unencrypted data the Online Trust Alliance (OTA). transmission of personal and sensitive in- formation including but not limited to user OTA researchers analyzed publicly reported ID and passwords. device vulnerabilities from November 2015 8. Lacking a sustainable and supportable through July 2016, and found the most glaring plan to address vulnerabilities through the failures were attributed to: product lifecycle including the lack of soft- ware/firmware update capabilities and/or insecure and untested security patches/ 1.
    [Show full text]
  • Cyber@UC Meeting 38
    Cyber@UC Meeting 38 Becoming a Certified Ethical Hacker If You’re New! ● Join our Slack ucyber.slack.com ● Feel free to get involved with one of our committees: Content, Finance, Public Affairs, Outreach, Recruitment ● Ongoing Projects: ○ Malware Sandboxing Lab ○ Cyber Range ○ RAPIDS Cyber Op Center Announcements ● P&G visit set for Jan 22nd 2-3pm ● We’re planning school visits, reach out! ● Logo designs welcome! Public Affairs ● Please fill out Google form for GroupMe Numbers! https://goo.gl/forms/94i9kMJgtpDGXsC22 ● Our brand new YouTube channel has just been made. We will be live streaming meetings, events, etc and posting relevant videos to the channel. Please subscribe! youtube.com/channel/UCWcJuk7A_1nDj4m-cHWvIFw Follow us on our social media: Facebook: facebook.com/CyberAtUC/ Twitter: twitter.com/UCyb3r Instagram: instagram.com/cyberatuc/ Website: gauss.ececs.uc.edu/UC.yber/ Weekly Content Botnets targets ARC Processors ● What is an ARC Processor? ○ ARC stands for Argonaut RISC Core ○ 32-bit CPUs popularly used for SoC devices ○ World’s second most popular CPU core ○ In more than 2 billion products every year ● A new variant of the Mirai botnet has been found that hijacks insecure devices using ARC processors, known as Mirai Okiru ● Discovered by the MalwareMustDie team, a malware research group ● ARC processor malware is apparently very uncommon ● This malware is similar to another version of Mirai that targeted MIPS and ARM processors Mirai Okiru (continued) ● The malware used is known as Linux/Mirai ELF ● ELF malware is very
    [Show full text]
  • An Accidental Discovery of Iot Botnets and a Method for Investigating Them with a Custom Lua Dissector
    2017 Annual ADFSL Conference on Digital Forensics, Security and Law Proceedings May 15th, 10:00 AM An Accidental Discovery of IoT Botnets and a Method for Investigating Them With a Custom Lua Dissector Max Gannon University of Alabama, Birmingham, [email protected] Gary Warner University of Alabama, Birmingham, [email protected] Arsh Arora University of Alabama, Birmingham, [email protected] Follow this and additional works at: https://commons.erau.edu/adfsl Part of the Digital Communications and Networking Commons, Forensic Science and Technology Commons, Information Security Commons, OS and Networks Commons, Other Computer Engineering Commons, and the Other Computer Sciences Commons Scholarly Commons Citation Gannon, Max; Warner, Gary; and Arora, Arsh, "An Accidental Discovery of IoT Botnets and a Method for Investigating Them With a Custom Lua Dissector" (2017). Annual ADFSL Conference on Digital Forensics, Security and Law. 3. https://commons.erau.edu/adfsl/2017/papers/3 This Peer Reviewed Paper is brought to you for free and open access by the Conferences at Scholarly Commons. It has been accepted for inclusion in Annual ADFSL Conference on Digital Forensics, Security and Law by an (c)ADFSL authorized administrator of Scholarly Commons. For more information, please contact [email protected]. An Accidental Discovery of IoT Botnets and ... CDFSL Proceedings 2017 AN ACCIDENTAL DISCOVERY OF IOT BOTNETS AND A :METHOD FOR INVESTIGATING THEM WITH A CUSTOM LUA DISSECTOR Max Gannon, Gary Warner, Arsh Arora University of Alabama at Birmingham 1201 University Blvd, Birmingham, AL 35233 {gannonm, gar, ararora}@uab.edu ABSTRACT This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets.
    [Show full text]
  • Decade of the Rats Threat Report
    Decade of the Cross-Platform APT Espionage Attacks Targeting Linux, Windows and Android Table of Contents Executive Summary ................................................................................................3 Lancer – An Installation Script ..................................................................................20 PWNLNX5 – The Controller .......................................................................................22 Key Findings ...........................................................................................................5 Another Linux Oddity — CASPER Mirai Variant .........................................................23 Strategic Intelligence Assessments: ........................................................................... 5 Tactical Intelligence Assessments: ............................................................................ 6 Cellular Division ...................................................................................................24 PWNDROID4 ..............................................................................................................24 Why the Targeting of Linux Systems Matters ..........................................................7 An Interesting Find .....................................................................................................26 The Linux Advantage ..............................................................................................8 CASPER Goes Mobile – PWNDROID5 .......................................................................27
    [Show full text]
  • Turning Internet of Things(Iot) Into Internet of Vulnerabilities (Iov) : Iot Botnets
    TURNING IOT INTO IOV : IOT BOTNETS 1 Turning Internet of Things(IoT) into Internet of Vulnerabilities (IoV) : IoT Botnets Kishore Angrishi Abstract—Internet of Things (IoT) is the next big evolutionary step in the world of internet. The main intention behind the IoT is to enable safer living and risk mitigation on different levels of life. Home Automation / With the advent of IoT botnets, the view towards IoT devices Smart Home has changed from enabler of enhanced living into Internet of vulnerabilities for cyber criminals. IoT botnets has exposed two Industrial Control Systems different glaring issues, 1) A large number of IoT devices are Smart City accessible over public Internet. 2) Security (if considered at all) is often an afterthought in the architecture of many wide spread Internet of Things (IoT) IoT devices. In this article, we briefly outline the anatomy of Autonomous the IoT botnets and their basic mode of operations. Some of the Vehicles Medical and healthcare major DDoS incidents using IoT botnets in recent times along Smart traffic & parking with the corresponding exploited vulnerabilities will be discussed. control We also provide remedies and recommendations to mitigate IoT Smart Metering & related cyber risks and briefly illustrate the importance of cyber Smart Grids insurance in the modern connected world. Index Terms—DDoS, IoT, IoT Botnets, Mirai Botnet, Cyber Insurance, Security I. INTRODUCTION Fig. 1. Internet of Things (IoT) The Internet of Things (IoT) is key in the digital world of connected living. The futuristic appeal to make life bit more enjoyable in a hectic day-to-day routine is enticing to many.
    [Show full text]
  • Mirai – Inside of an Iot Botnet
    Mirai – Inside of an IoT Botnet Ron Winward Security Evangelist, Americas February 7, 2017 Agenda • What this is… • A study of the Mirai structure, components, and aack vectors • A focus on the network aspects of the botnet • What this isn’t… • A code review • A how-to guide 2 Mirai Overview 3 Mirai source code released on HackForums.net • By Anna-senpai on Sep 30, 2016 • From posts and replies in the thread Anna-senpai used it for the aack on Krebs and OVH. • Some users doubNng the authenNcity of Anna-senpai, but high reputaon users acknowledged his capabiliNes 4 $$$ Efficient bot harves>ng Create account Exists ? + Assign bots - Loader and Bot wri7en in C C2 API - ScanListen and CnC service in Go ScanListen CnC - Scalable, distributed services New vic! - TargeNng BusyBox based devices 48101 23 - 60+ factory default passwords Load Svc CnC Connect Report IP + credenNals Load bot Telnet port scan Telnet port scans Bot new vicBot Telnet port scans (infected device) (infected device) Brute force login 5 Mirai predefined creden>als for brung 6 Aack Vectors 7 Mirai Easter Eggs 8 Mirai Easter Eggs I love chicken nuggets 9 Lab Setup 10 Lab Network Topology 192.168.3.2 X 192.168.3.1/24 192.168.1.1/24 192.168.2.1/24 Linksys WRT54GL/ Tomato Sricam AP003 Eth0: 192.168.3.140 ESXI Ens33: Eth1: Eth0: Eth0: Eth0: Enp2s0: 192.168.2.10 192.168.2.53 192.168.2.11 192.168.2.12 192.168.2.16 192.168.3.10 util1 ns1 cnc scanrec bot2 Target ubuntu ubuntu debian debian raspbian ubuntu Ens32: Eth0: Enp3s6: 192.168.1.4 192.168.1.53 192.168.1.8 11 management My test
    [Show full text]
  • Building a Honeypot to Research Cyber-Attack Techniques
    Building a Honeypot to Research Cyber-Attack Techniques Simon Bell, Computer Science BSc Candidate Number 18585 School of Engineering and Informatics Project Supervisor: Dr. Martin Berger University of Sussex, May 2014 Declaration This report is submitted as part requirement for the degree of Computer Science at the University of Sussex. It is the product of my own labour except where indicated in the text. The report may be freely copied and distributed provided the source is acknowledged. Signature: Simon Bell ii Acknowledgements The author wishes to thank Dr. Gareth Owen, University of Portsmouth for his input and advice on cybersecurity; Dr. Lorenzo Cavallaro, Royal Holloway, University of London for the online course on malware and advice during the project and Dr. Martin Berger for his encouragement, advice and support while supervising the project. UNIVERSITY OF SUSSEX Simon Bell, Computer Science BSc Building a Honeypot to Research Cyber-Attack Techniques Summary The internet can be a dark and dangerous place; featuring viruses and cyber attacks. This project aims to uncover some of these threats and reveal just how vulnerable the inter- net can be. The project involves creating a honeypot - a device designed to attract cyber attackers - and to analyse cyber attacks to see what is going on in the dark underworld of the internet. This dissertation explains the process involved in building a honeypot in the program- ming language C along with the results produced from that honeypot. Malicious files up- loaded to the honeypot will be analyses to gain an understanding into how cyber-attackers carry out certain types of attacks.
    [Show full text]
  • F-Secure Threat Report H1 2014
    THREAT REPORT H1 2014 SWITCH ON FREEDOM www.f-secure.com 1 CONTENTS CONTENTS 2 AT A GLANCE 3 FOREWORD 4 TOP-10 DETECTIONS DOWNADUP (aka OF NOTE CONFICKER) 5 This six years old worm exploits the MS08-067 vulnerability in Windows. It spreads over the Internet and through removable media and INCIDENTS CALENDAR 6 network shares. rounded up by... THREAT LANDSCAPE SUMMARY 8 SALITY TOP-10 DETECTIONS 9,11 MOBILE MALWARE 12 MAC MALWARE 14 SOURCES 15 H1 2014 THREAT REPORT AT A GLANCE... JANUARY FEBRUARY MARCH APRIL MAY JUNE iOS updates Coremax FBI hunts down released to fix extension does Gameover Zeus’ major SSL flaw browser hijacking mastermind Active attacks Windows XP Police ‘Oleg Pliss’ using new IE reaches official ransomware hackers arrested 0-day bug end of life (EOL) moves to Android in Moscow INCIDENTS CALENDAR Page 2014 6 +201138N MAJAVA, 11% 31 MALWARE PC MALWARE Page 12 TOP-10 DETECTIONS WEB-BASED ATTACKS, 20% MOBILE Page 9, 11 Android continues to be a favorite target for majority of the Windows threat landscape is filled with mobile threats. But threats directed towards iOS do exist, even if there are far fewer of them. existing malware families—some of which OTHERS, 38% has been around for years, being kept alive by unpatched machines. ANDROID + iOS DOWNADUP/ CONFICKER, 31% 1 FAMILYnew NEW SSLCREDTHIEF TOP-10 DETECTIONS 294 Signed library file FAMILIES DOWNADUP (aka WEB-BASED ATTACKS MAJAVA listens to outgoing SSL connections to CONFICKER) A collection of malware, A collection of exploits against VARIANTSor This six years old worm techniques, or exploits used vulnerabilities in the Java steal Apple ID and exploits the MS08-067 to redirect the web browser development platform.
    [Show full text]
  • White-Hat Worm to Fight Malware and Its Evaluation by Agent-Oriented Petri Nets †
    sensors Article White-Hat Worm to Fight Malware and Its Evaluation by Agent-Oriented Petri Nets † Shingo Yamaguchi Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Ube 755-8611, Japan; [email protected] † This paper is an extended version of our paper published in Yamaguchi, S. Modeling and Evaluation of IoT Worm with Lifespan and Secondary Infectivity by Agent-Oriented Petri Net PN2. In Proceeding of the IEEE 6th International Conference on Consumer Electronics – Taiwan (IEEE 2019 ICCE-TW), Yilan, Taiwan, 20–22 May 2019. Received: 23 December 2019; Accepted: 16 January 2020; Published: 19 January 2020 Abstract: A new kind of malware called Mirai is spreading like wildfire. Mirai is characterized by targeting Internet of Things (IoT) devices. Since IoT devices are increasing explosively, it is not realistic to manage their vulnerability by human-wave tactics. This paper proposes a new approach that uses a white-hat worm to fight malware. The white-hat worm is an extension of an IoT worm called Hajime and introduces lifespan and secondary infectivity (the ability to infect a device infected by Mirai). The proposed white-hat worm was expressed as a formal model with agent-oriented Petri nets called PN2. The model enables us to simulate a battle between the white-hat worm and Mirai. The result of the simulation evaluation shows that (i) the lifespan successfully reduces the worm’s remaining if short; (ii) if the worm has low secondary infectivity, its effect depends on the lifespan; and (iii) if the worm has high secondary infectivity, it is effective without depending on the lifespan.
    [Show full text]